snowflake-snowpark-python
Snowflake Snowpark for Python
Decision gist · record as of 2026-08-14
Yes. Snowpark Python is actively maintained, has low install friction, carries a permissive Apache 2.0 license, and solves a real problem for teams working with Snowflake—enabling in-warehouse computation without data movement. It ranks in the top 1000 PyPI packages by download volume and has no known security vulnerabilities. Install it if you use Snowflake and want to process data without moving it to your application layer.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Snowflake account with valid connection credentials (account, user, password, role, warehouse, database, schema).
- Python 3.10+ required; Snowpark pandas requires Python 3.10 or 3.11.
- Low friction installation via pip.
License · maintenance · safety
Apache License, Version 2.0 (permissive) — Licensed under Apache License 2.0 (permissive), which allows commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
last release 2026-07-29 (16 days) · last repo commit 2026-08-13 · 339 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 100,681,113 downloads/mo, #343 on PyPI
Alternatives
Verify before relying
pip install snowflake-snowpark-python
from snowflake.snowpark import Session
connection_parameters = {
"account": "your_account",
"user": "your_user",
"password": "your_password",
"role": "your_role",
"warehouse": "your_warehouse",
"database": "your_database",
"schema": "your_schema"
}
session = Session.builder.configs(connection_parameters).create()
df = session.create_dataframe([[1, 2], [3, 4]], schema=["a", "b"])
df = df.filter(df.a > 1)
result = df.collect()- Performance characteristics and scalability limits for large datasets or complex transformations.
- Whether UDF support mentioned in the description requires additional setup beyond the base installation.
- Compatibility with specific Snowflake editions or feature availability tiers.
What it is and what it does
Snowpark Python is a library that lets you build data processing applications that run computations directly in Snowflake's cloud warehouse, eliminating the need to download data locally. It provides two main interfaces: a native Snowpark API for building data pipelines using dataframe-like operations, and an optional Snowpark pandas API (via modin) that mimics the familiar pandas interface for users already comfortable with that ecosystem.
The library handles the translation of your Python code into SQL that executes in Snowflake, managing the session connection, data serialization, and result collection. It supports standard dataframe operations like filtering, aggregation, and joins, as well as reading from and writing to both Snowflake tables and local pandas DataFrames. The package depends on snowflake-connector-python for the underlying connection layer and includes utilities for serialization (cloudpickle), configuration (pyyaml), and timezone handling (tzlocal).
Use it for
- Build ETL pipelines that transform and load data directly in Snowflake without staging data locally.
- Analyze large datasets using familiar dataframe syntax while keeping computation in the cloud warehouse.
- Convert pandas-based data workflows to run in Snowflake by using the Snowpark pandas API with minimal code changes.
- Develop machine learning feature engineering steps that execute server-side, reducing data movement and latency.
- Create scheduled data processing jobs that query, filter, and aggregate Snowflake tables programmatically.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Snowpark Python is actively maintained, has low install friction, carries a permissive Apache 2.0 license, and solves a real problem for teams working with Snowflake—enabling in-warehouse computation without data movement. It ranks in the top 1000 PyPI packages by download volume and has no known security vulnerabilities. Install it if you use Snowflake and want to process data without moving it to your application layer.
Install
snowflake-snowpark-python on PyPI
Before you install
Low friction installation via pip. The package is actively maintained with a release 16 days old and an active repository. Nine runtime dependencies are all standard Python packages (setuptools, wheel, snowflake-connector-python, typing-extensions, pyyaml, cloudpickle, protobuf, python-dateutil, tzlocal).
Requires a Snowflake account with valid connection credentials (account, user, password, role, warehouse, database, schema). Python 3.10+ required; Snowpark pandas requires Python 3.10 or 3.11.
License in practice
Licensed under Apache License 2.0 (permissive), which allows commercial use, modification, and distribution with minimal restrictions—suitable for most production and proprietary projects.
Quickstart
pip install snowflake-snowpark-python
from snowflake.snowpark import Session
connection_parameters = {
"account": "your_account",
"user": "your_user",
"password": "your_password",
"role": "your_role",
"warehouse": "your_warehouse",
"database": "your_database",
"schema": "your_schema"
}
session = Session.builder.configs(connection_parameters).create()
df = session.create_dataframe([[1, 2], [3, 4]], schema=["a", "b"])
df = df.filter(df.a > 1)
result = df.collect()Verify before relying
- Performance characteristics and scalability limits for large datasets or complex transformations.
- Whether UDF support mentioned in the description requires additional setup beyond the base installation.
- Compatibility with specific Snowflake editions or feature availability tiers.
Package facts
| License | Apache License, Version 2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagessetuptoolswheelsnowflake-connector-pythontyping-extensionspyyamlcloudpickleprotobufpython-dateutiltzlocal |
| Maintenance | Actively maintained 16 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 100,681,113 / month, #343 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Other EnvironmentIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Information TechnologyIntended Audience :: System AdministratorsLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: SQLTopic :: DatabaseTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software DevelopmentTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Application FrameworksTopic :: Software Development :: Libraries :: Python Modules |
Evidence: snowflake_snowpark_python-1.54.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “snowflake data processing”
- snowflake-snowpark-pythonSnowpark Python provides APIs to query and process data directly in…
- snowflake-telemetry-pythonEmits telemetry data from Python UDFs, UDTFs, and Stored Procedures…
- prefect-snowflakePrefect integration that provides tasks and blocks for connecting…
Give your agent the search over MCP, or paste the wish link into any chat.
More Software Development packages
Provides backported and experimental type hints for Python 3.9+, allowing use of newer typing features on older Python versions and enabling early experimentation with type system PEPs before they enter the standard library.
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides a way to document function parameters, class attributes, return types, and variables inline using Python's `Annotated` type hint syntax instead of traditional docstrings.
Typer builds command-line applications from Python functions using type hints, automatically generating help text, argument parsing, and shell completion.
Install it if you are building CLIs in Python.
Distlib provides low-level packaging utilities for building, distributing, and managing Python software—including metadata handling, version specifiers, wheel support, script installation, and dependency resolution.
See also snowflake · snowpark-connect · snowflake-ml-python · snowflake-cli · dagster-snowflake-pandas · snowpark-connect-deps-2 · apache-airflow-providers-snowflake · snowflake-connector-python · cuallee · snowpark-connect-deps-1